Personalized Medicine

Personalized Medicine: The Background

Personalized medicine is an extension of traditional approaches to understanding and treating illness. Since the beginning of the study of medicine, physicians have employed evidence found through observation to make a diagnosis or to prescribe treatment. In the past, this was presumably tailored to each individual, but personalized medicine makes treatment more specific.

In the modern conception of personalized medicine, the tools provided to the physician are more precise, probing not just the obvious, such as a tumor on a mammogram or cells under a microscope, but the very molecular makeup of each patient. Looking at the patient on this level helps the physician get a profile of the patient’s genetic distinction, or mapping. By investigating this genetic mapping, medical professionals are then able to profile patients, and use the found information to plan out a course of treatment that is much more in step with the way their body works. Genomic medicine and personalized medicine use genetic information to prevent or treat disease in adults or their children.

What Can We Gain from a Genetic Map?

Having a genetic map or a profile of a patient’s genetic variation can then guide the selection of drugs or treatment processes. This can be used to minimize side effects or to create a strategy for a more successful outcome from the medical treatment. Helping the physician cover all the bases is imperative. Genetic mapping can also indicate the propensity to contract certain diseases before the patient actually shows recognizable symptoms, allowing the physician and patient to put together a plan for observation and prevention.

The ability to profile how genes are put together in sequence and expression level is helping to redefine the ways in which medical professionals classify diseases and discover treatments, allowing physicians to go beyond the "one size fits all" model that may be ineffective or have undesirable side effects. Through further organization, and the use of personalized medicine, medical professionals are developing many sub populations for complex diseases and physical conditions such as these.

Diabetes

Alzheimers

Cancer

Heart Disease

Personalized medicine may be able to help the medical community make the most effective clinical decisions for each patient on an individual level.

Personalized Medicine: Helping to Organize the Fight against Disease

Personalized medicine, when coupled with personal pharmacogenetics, is a unique approach that may be well suited for the health challenges we face in the new millennium. Although the medical and scientific communities, through research and discovery, got the upper hand over many of the diseases we’ve encountered since the advent of advanced medicine, we are still threatened by many more complicated diseases.

Diseases like Diabetes, heart disease, cancer and Alzheimer’s are thought to caused by a combination of genetic and other factors. Coupled with the fact that they tend to be chronic, they place a significant burden on not only the patient, but on the healthcare system as a whole. Personalized medicine aims to provide the tools and knowledge to fight chronic diseases and treat them more effectively than ever before.

Genetic profiles can help physicians to better discern subgroups of patients with various forms of cancer in addition to other complex diseases, helping to guide doctors with accurate forms of predictive medicine and preventative medicine. With personalized medicine, the physician is intending to select the best treatment protocol or even, in many cases, avoid passing the expense and risks of unnecessary medical treatments on to the patient altogether. Also, personalized medicine, when used correctly, aims to guide tests that detect variation in the way individual patients metabolize various pharmaceuticals. Personalized medicine is working to help determine the right dose for a patient, helping to avoid hazards based on familial history, environmental influences, and genetic variation.